BACKGROUND: Clinical decision making for patients with intraductal papillary mucinous neoplasms (IPMN) of the pancreas is challenging. Even with strict criteria for resection, most resected lesions lack high-grade dysplasia (HGD) or invasive carcinoma. METHODS: We evaluated patients who underwent resection of histologically confirmed IPMN and had preoperative imaging available for review. A hepatobiliary radiologist blinded to histopathologic subtype reviewed preoperative imaging and recorded cyst characteristics. Patients with mixed-type IPMN were grouped with main-duct lesions for this analysis. Based on an ordinal logistic regression model, we devised two independent nomograms to predict the findings of adenoma, high-grade dysplasia (HGD-CIS), and invasive carcinoma, separately in both main and branch-duct IPMN. Bootstrap validation was used to evaluate the performance of these models, and a concordance index was derived from this internal validation. RESULTS: There were 219 patients who met criteria for this study. Branch-duct IPMN (bdIPMN) comprised 56 % of the resected lesions. The proportion of HGD-CIS was 15 % for bdIPMN and 33 % for main-duct lesions (mdIPMN); P = 0.003. Invasive carcinoma was identified in 15 % of bdIPMN and 41 % of main-duct lesions (P < 0.001). On multivariate regression, patient gender, history of prior malignancy, presence of solid component, and weight loss were found to be significantly associated with the ordinal outcome for patients with mdIPMN and built into the nomogram (concordance index 0.74). For patients with bdIPMN weight loss, solid component, and lesion diameter were associated with the outcome; (concordance index 0.74). CONCLUSION: Based on the analysis of patients selected for resection, two nomograms were created that predict a patient's individual likelihood of harboring HGD or invasive malignancy in radiologically diagnosed IPMN. External validation is ongoing.
BACKGROUND: Clinical decision making for patients with intraductal papillary mucinous neoplasms (IPMN) of the pancreas is challenging. Even with strict criteria for resection, most resected lesions lack high-grade dysplasia (HGD) or invasive carcinoma. METHODS: We evaluated patients who underwent resection of histologically confirmed IPMN and had preoperative imaging available for review. A hepatobiliary radiologist blinded to histopathologic subtype reviewed preoperative imaging and recorded cyst characteristics. Patients with mixed-type IPMN were grouped with main-duct lesions for this analysis. Based on an ordinal logistic regression model, we devised two independent nomograms to predict the findings of adenoma, high-grade dysplasia (HGD-CIS), and invasive carcinoma, separately in both main and branch-duct IPMN. Bootstrap validation was used to evaluate the performance of these models, and a concordance index was derived from this internal validation. RESULTS: There were 219 patients who met criteria for this study. Branch-duct IPMN (bdIPMN) comprised 56 % of the resected lesions. The proportion of HGD-CIS was 15 % for bdIPMN and 33 % for main-duct lesions (mdIPMN); P = 0.003. Invasive carcinoma was identified in 15 % of bdIPMN and 41 % of main-duct lesions (P < 0.001). On multivariate regression, patient gender, history of prior malignancy, presence of solid component, and weight loss were found to be significantly associated with the ordinal outcome for patients with mdIPMN and built into the nomogram (concordance index 0.74). For patients with bdIPMN weight loss, solid component, and lesion diameter were associated with the outcome; (concordance index 0.74). CONCLUSION: Based on the analysis of patients selected for resection, two nomograms were created that predict a patient's individual likelihood of harboring HGD or invasive malignancy in radiologically diagnosed IPMN. External validation is ongoing.
Authors: Mohammad A Al Efishat; Marc A Attiyeh; Anne A Eaton; Mithat Gönen; Denise Prosser; Anna E Lokshin; Carlos Fernández-Del Castillo; Keith D Lillemoe; Cristina R Ferrone; Ilaria Pergolini; Mari Mino-Kenudson; Neda Rezaee; Marco Dal Molin; Matthew J Weiss; John L Cameron; Ralph H Hruban; Michael I D'Angelica; T Peter Kingham; Ronald P DeMatteo; William R Jarnagin; Christopher L Wolfgang; Peter J Allen Journal: Ann Surg Date: 2018-08 Impact factor: 12.969
Authors: Eran Sadot; Olca Basturk; David S Klimstra; Mithat Gönen; Anna Lokshin; Richard Kinh Gian Do; Michael I D'Angelica; Ronald P DeMatteo; T Peter Kingham; William R Jarnagin; Peter J Allen Journal: Ann Surg Date: 2015-12 Impact factor: 12.969
Authors: Marc A Attiyeh; Carlos Fernández-Del Castillo; Mohammad Al Efishat; Anne A Eaton; Mithat Gönen; Ruqayyah Batts; Ilaria Pergolini; Neda Rezaee; Keith D Lillemoe; Cristina R Ferrone; Mari Mino-Kenudson; Matthew J Weiss; John L Cameron; Ralph H Hruban; Michael I D'Angelica; Ronald P DeMatteo; T Peter Kingham; William R Jarnagin; Christopher L Wolfgang; Peter J Allen Journal: Ann Surg Date: 2018-01 Impact factor: 12.969
Authors: Jayasree Chakraborty; Abhishek Midya; Lior Gazit; Marc Attiyeh; Liana Langdon-Embry; Peter J Allen; Richard K G Do; Amber L Simpson Journal: Med Phys Date: 2018-09-27 Impact factor: 4.071
Authors: Kate A Harrington; Travis L Williams; Sharon A Lawrence; Jayasree Chakraborty; Mohammad A Al Efishat; Marc A Attiyeh; Gokce Askan; Yuting Chou; Alessandra Pulvirenti; Caitlin A McIntyre; Mithat Gonen; Olca Basturk; Vinod P Balachandran; T Peter Kingham; Michael I D'Angelica; William R Jarnagin; Jeffrey A Drebin; Richard K Do; Peter J Allen; Amber L Simpson Journal: J Med Imaging (Bellingham) Date: 2020-06-25
Authors: Anne Marie Lennon; Lindsey L Manos; Ralph H Hruban; Syed Z Ali; Elliot K Fishman; Ihab R Kamel; Siva P Raman; Atif Zaheer; Susan Hutfless; Ashley Salamone; Vandhana Kiswani; Nita Ahuja; Martin A Makary; Matthew J Weiss; Kenzo Hirose; Michael Goggins; Christopher L Wolfgang Journal: Ann Surg Oncol Date: 2014-05-08 Impact factor: 5.344